Early Serial Assessment of Aggregate Vasoactive Support and Mortality in Cardiogenic Shock: Insights from the Critical Care Cardiology Trials Network Registry.

Background: Associations of early changes in vasoactive support with cardiogenic shock (CS) mortality remain incompletely defined. Methods: The Critical Care Cardiology Trials Network is a multicenter registry of cardiac intensive care units (CICUs). Patients admitted with CS (2018-2023) had vasoactive dosing assessed at 4 and 24 hours (h) from CICU admission and quantified by the vasoactive-inotropic score (VIS). Prognostic associations of VIS at both timepoints, as well as change in VIS from 4h to 24h, were examined. Interaction testing was performed by mechanical circulatory support (MCS) status. Results: Among 3,665 patients, 82% had a change in VIS <10, with 7% and 11% having a ≥10point increase and decrease from 4h to 24h, respectively. The 4h and 24h VIS were each associated with CICU mortality (13%- 45% and 11%-73% for VIS <10 to ≥40, respectively; ptrend <0.0001 for each). Stratifying by the 4h VIS, changes in VIS from 4h to 24h had a graded association with mortality, ranging from a 2-to->4-fold difference in mortality comparing those with a ≥10-point increase to a ≥10-point decrease in VIS (p-trend <0.0001). The change in VIS alone provided good discrimination of CICU mortality (C-statistic 0.72 [95% CI 0.70-0.75]), and improved discrimination of the 24h SOFA score (0.76 [95% CI 0.74-0.78] from 0.72 [95% CI 0.69-0.74]) and the clinician-assessed SCAI stage (0.77 [95% CI 0.75-0.79] from 0.72 [95% CI 0.70-0.74]). Although present in both groups, the mortality risk associated with VIS was attenuated in patients managed with vs. without MCS (OR per 10-point higher 24h VIS: 1.36 [1.23-1.49] vs. 1.84 [1.69-2.01]; p-interaction<0.0001). Conclusions: Early changes in the magnitude of vasoactive support in CS are associated with a gradient of risk for mortality. These data suggest that early VIS trajectory may improve CS prognostication, with potential to be leveraged for clinical decision-making and research applications in CS.

Cloud-Based Machine Learning Platform to Predict Clinical Outcomes at Home for Patients With Cardiovascular Conditions Discharged From Hospital: Clinical Trial.

BACKGROUND: Hospitalizations account for almost one-third of the US $4.1 trillion health care cost in the United States. A substantial portion of these hospitalizations are attributed to readmissions, which led to the establishment of the Hospital Readmissions Reduction Program (HRRP) in 2012. The HRRP reduces payments to hospitals with excess readmissions. In 2018, >US $700 million was withheld; this is expected to exceed US $1 billion by 2022. More importantly, there is nothing more physically and emotionally taxing for readmitted patients and demoralizing for hospital physicians, nurses, and administrators. Given this high uncertainty of proper home recovery, intelligent monitoring is needed to predict the outcome of discharged patients to reduce readmissions. Physical activity (PA) is one of the major determinants for overall clinical outcomes in diabetes, hypertension, hyperlipidemia, heart failure, cancer, and mental health issues. These are the exact comorbidities that increase readmission rates, underlining the importance of PA in assessing the recovery of patients by quantitative measurement beyond the questionnaire and survey methods. OBJECTIVE: This study aims to develop a remote, low-cost, and cloud-based machine learning (ML) platform to enable the precision health monitoring of PA, which may fundamentally alter the delivery of home health care. To validate this technology, we conducted a clinical trial to test the ability of our platform to predict clinical outcomes in discharged patients. METHODS: Our platform consists of a wearable device, which includes an accelerometer and a Bluetooth sensor, and an iPhone connected to our cloud-based ML interface to analyze PA remotely and predict clinical outcomes. This system was deployed at a skilled nursing facility where we collected >17,000 person-day data points over 2 years, generating a solid training database. We used these data to train our extreme gradient boosting (XGBoost)-based ML environment to conduct a clinical trial, Activity Assessment of Patients Discharged from Hospital-I, to test the hypothesis that a comprehensive profile of PA would predict clinical outcome. We developed an advanced data-driven analytic platform that predicts the clinical outcome based on accurate measurements of PA. Artificial intelligence or an ML algorithm was used to analyze the data to predict short-term health outcome. RESULTS: We enrolled 52 patients discharged from Stanford Hospital. Our data demonstrated a robust predictive system to forecast health outcome in the enrolled patients based on their PA data. We achieved precise prediction of the patients' clinical outcomes with a sensitivity of 87%, a specificity of 79%, and an accuracy of 85%. CONCLUSIONS: To date, there are no reliable clinical data, using a wearable device, regarding monitoring discharged patients to predict their recovery. We conducted a clinical trial to assess outcome data rigorously to be used reliably for remote home care by patients, health care professionals, and caretakers.

Enhancing the Prediction of Cardiac Allograft Vasculopathy Using Intravascular Ultrasound and Machine Learning: A Proof of Concept.

BACKGROUND: Cardiac allograft vasculopathy (CAV) is the leading cause of late graft dysfunction in heart transplantation. Building on previous unsupervised learning models, we sought to identify CAV clusters using serial maximal intimal thickness and baseline clinical risk factors to predict the development of early CAV. METHODS: This is a single-center retrospective study including adult heart transplantation recipients. A latent class mixed-effects model was used to identify patient clusters with similar trajectories of maximal intimal thickness posttransplant and pretransplant covariates associated with each cluster. RESULTS: Among 186 heart transplantation recipients, we identified 4 patient phenotypes: very low, low, moderate, and high risk. The 5-year risk (95% CI) of the International Society for Heart and Lung Transplantation-defined CAV in the high, moderate, low, and very low risk groups was 49.1% (35.2%-68.5%), 23.4% (13.3%-41.2%), 5.0% (1.3%-19.6%), and 0%, respectively. Only patients in the moderate to high risk cluster developed the International Society for Heart and Lung Transplantation CAV 2-3 at 5 years (P=0.02). Of the 4 groups, the low risk group had significantly younger female recipients, shorter ischemic time, and younger female donors compared with the high risk group. CONCLUSIONS: We identified 4 clusters characterized by distinct maximal intimal thickness trajectories. These clusters were shown to discriminate against the development of angiographic CAV. This approach allows for the personalization of surveillance and CAV-directed treatment before the development of angiographically apparent disease.

Interhospital Variation in Admissions Managed With Critical Care Therapies or Invasive Hemodynamic Monitoring in Tertiary Cardiac Intensive Care Units: An Analysis From the Critical Care Cardiology Trials Network Registry.

BACKGROUND: Wide interhospital variations exist in cardiovascular intensive care unit (CICU) admission practices and the use of critical care restricted therapies (CCRx), but little is known about the differences in patient acuity, CCRx utilization, and the associated outcomes within tertiary centers. METHODS: The Critical Care Cardiology Trials Network is a multicenter registry of tertiary and academic CICUs in the United States and Canada that captured consecutive admissions in 2-month periods between 2017 and 2022. This analysis included 17 843 admissions across 34 sites and compared interhospital tertiles of CCRx (eg, mechanical ventilation, mechanical circulatory support, continuous renal replacement therapy) utilization and its adjusted association with in-hospital survival using logistic regression. The Pratt index was used to quantify patient-related and institutional factors associated with CCRx variability. RESULTS: The median age of the study population was 66 (56-77) years and 37% were female. CCRx was provided to 62.2% (interhospital range of 21.3%-87.1%) of CICU patients. Admissions to CICUs with the highest tertile of CCRx utilization had a greater burden of comorbidities, had more diagnoses of ST-elevation myocardial infarction, cardiac arrest, or cardiogenic shock, and had higher Sequential Organ Failure Assessment scores. The unadjusted in-hospital mortality (median, 12.7%) was 9.6%, 11.1%, and 18.7% in low, intermediate, and high CCRx tertiles, respectively. No clinically meaningful differences in adjusted mortality were observed across tertiles when admissions were stratified by the provision of CCRx. Baseline patient-level variables and institutional differences accounted for 80% and 5.3% of the observed CCRx variability, respectively. CONCLUSIONS: In a large registry of tertiary and academic CICUs, there was a >4-fold interhospital variation in the provision of CCRx that was primarily driven by differences in patient acuity compared with institutional differences. No differences were observed in adjusted mortality between low, intermediate, and high CCRx utilization sites.

Changing Strategy Between Bridge to Transplant and Destination LVAD Therapy After the First 3 Months: Analysis of the STS-INTERMACS Database.

BACKGROUND: Left ventricular assist devices (LVADs) have been implanted as bridge to transplantation (BTT), bridge to candidacy (BTC) or destination therapy (DT) on the basis of relative and absolute contraindications to transplantation. Multiple factors may lead to changes in the strategy of support after LVAD implantation. METHODS: Based on INTERMACS (Interagency Registry for Mechanically Assisted Circulatory Support) 2012-2020 data, 11,262 patients survived to 3 months on continuous-flow LVADs with intent of BTT or DT. Preimplant characteristics and early events post-LVAD were analyzed in relation to changes in BTT or DT strategy during the next 12 months. RESULTS: Among 3216 BTT patients at 3 months, later transplant delisting or death without transplant occurred in 536 (16.7%) and was more common with age, profiles 1-2, renal dysfunction, and independently for prior cardiac surgery (HR 1.25, 95% CI 1.04-1.51; P = 0.02). Post-LVAD events of infections, gastrointestinal bleeding, stroke, and right heart failure as defined by inotropic therapy, predicted delisting and death, as did in-hospital location at 3 months (HR 1.67, 95% CI 1.20-2.33; P = 0.0024). Of 8046 patients surviving to 3 months with the intent of destination therapy, 750 (9.3%) subsequently underwent listing or transplantation, often with initial histories of acute HF (HR 1.70, 95% CI 1.27-2.27; P = 0.0012) or malnutrition-cachexia (1.73, 95% CI 1.14-2.63; P = 0.0099). Multiple gastrointestinal bleeding events (≥ 4) with LVAD increased transition from BTT to DT (HR 4.22, 95% CI 1.46-12.275; P = 0.0078) but also from DT to BTT (HR 5.17, 95% CI 1.92-13.9; P = 0.0011). CONCLUSIONS: Implant strategies change over time in relation to preimplant characteristics and adverse events post implant. Preimplant recognition of factors predicting later change in implant strategy will refine initial triage, whereas further reduction of post-LVAD complications will expand options, including eventual consideration of heart transplantation.

Prognostic significance of haemodynamic parameters in patients with cardiogenic shock.

AIMS: Invasive haemodynamic assessment with a pulmonary artery catheter is often used to guide the management of patients with cardiogenic shock (CS) and may provide important prognostic information. We aimed to assess prognostic associations and relationships to end-organ dysfunction of presenting haemodynamic parameters in CS. METHODS AND RESULTS: The Critical Care Cardiology Trials Network is an investigator-initiated multicenter registry of cardiac intensive care units (CICUs) in North America coordinated by the TIMI Study Group. Patients with CS (2018-2022) who underwent invasive haemodynamic assessment within 24 h of CICU admission were included. Associations of haemodynamic parameters with in-hospital mortality were assessed using logistic regression, and associations with presenting serum lactate were assessed using least squares means regression. Sensitivity analyses were performed excluding patients on temporary mechanical circulatory support and adjusted for vasoactive-inotropic score. Among the 3603 admissions with CS, 1473 had haemodynamic data collected within 24 h of CICU admission. The median cardiac index was 1.9 (25th-75th percentile, 1.6-2.4) L/min/m2 and mean arterial pressure (MAP) was 74 (66-86) mmHg. Parameters associated with mortality included low MAP, low systolic blood pressure, low systemic vascular resistance, elevated right atrial pressure (RAP), elevated RAP/pulmonary capillary wedge pressure ratio, and low pulmonary artery pulsatility index. These associations were generally consistent when controlling for the intensity of background pharmacologic and mechanical haemodynamic support. These parameters were also associated with higher presenting serum lactate. CONCLUSION: In a contemporary CS population, presenting haemodynamic parameters reflecting decreased systemic arterial tone and right ventricular dysfunction are associated with adverse outcomes and systemic hypoperfusion.

Pulmonary Artery Catheter Use and Mortality in the Cardiac Intensive Care Unit.

BACKGROUND: The appropriate use of pulmonary artery catheters (PACs) in critically ill cardiac patients remains debated. OBJECTIVES: The authors aimed to characterize the current use of PACs in cardiac intensive care units (CICUs) with attention to patient-level and institutional factors influencing their application and explore the association with in-hospital mortality. METHODS: The Critical Care Cardiology Trials Network is a multicenter network of CICUs in North America. Between 2017 and 2021, participating centers contributed annual 2-month snapshots of consecutive CICU admissions. Admission diagnoses, clinical and demographic data, use of PACs, and in-hospital mortality were captured. RESULTS: Among 13,618 admissions at 34 sites, 3,827 were diagnosed with shock, with 2,583 of cardiogenic etiology. The use of mechanical circulatory support and heart failure were the patient-level factors most strongly associated with a greater likelihood of the use of a PAC (OR: 5.99 [95% CI: 5.15-6.98]; P < 0.001 and OR: 3.33 [95% CI: 2.91-3.81]; P < 0.001, respectively). The proportion of shock admissions with a PAC varied significantly by study center ranging from 8% to 73%. In analyses adjusted for factors associated with their placement, PAC use was associated with lower mortality in all shock patients admitted to a CICU (OR: 0.79 [95% CI: 0.66-0.96]; P = 0.017). CONCLUSIONS: There is wide variation in the use of PACs that is not fully explained by patient level-factors and appears driven in part by institutional tendency. PAC use was associated with higher survival in cardiac patients with shock presenting to CICUs. Randomized trials are needed to guide the appropriate use of PACs in cardiac critical care.

Rethinking Donor and Recipient Risk Matching in Europe and North America: Using Heart Transplant Predictors of Donor and Recipient Risk.

BACKGROUND: In Europe, there is greater acceptance of hearts from higher-risk donors for transplantation, whereas in North America, the donor heart discard rate is significantly higher. A Donor Utilization Score (DUS) was used to compare European and North American donor characteristics for recipients included in the International Society for Heart and Lung Transplantation registry from 2000 to 2018. DUS was further evaluated as an independent predictor for 1-year freedom from graft failure, after adjusting for recipient risk. Lastly, we assessed donor-recipient risk matching with the outcome of 1-year graft failure. METHODS: DUS was applied to the International Society for Heart and Lung Transplantation cohort using meta-modeling. Posttransplant freedom from graft failure was summarized by Kaplan-Meier survival. Multivariable Cox proportional hazard regression was applied to quantify the effects of DUS and Index for Mortality Prediction After Cardiac Transplantation score on the 1-year risk of graft failure. We present 4 donor/recipient risk groups using the Kaplan-Meier method. RESULTS: European centers accept significantly higher-risk donor hearts compared to North America. DUS 0.45 versus 0.54, P<0.005). DUS was an independent predictor for graft failure with an inverse linear relationship when adjusted for covariates (P<0.001). The Index for Mortality Prediction After Cardiac Transplantation score, a validated tool to assess recipient risk, was also independently associated with 1-year graft failure (P<0.001). In North America, 1-year graft failure was significantly associated with donor-recipient risk matching (log-rank P<0.001). One-year graft failure was highest with pairing of high-risk recipients and donors (13.1% [95% CI, 10.7%-13.9%]) and lowest among low-risk recipients and donors (7.4% [95% CI, 6.8%-8.0%]). Matching of low-risk recipients with high-risk donors was associated with significantly less graft failure (9.0% [95% CI, 8.3%-9.7%]) than high-risk recipients with low-risk donors (11.4% [95% CI, 10.7%-12.2%]) Conclusions: European heart transplantation centers are more likely to accept higher-risk donor hearts than North American centers. Acceptance of borderline-quality donor hearts for lower-risk recipients could improve donor heart utilization without compromising recipient survival.

PROMIS: Physical, Mental and Social Health Outcomes Improve From Before to Early After LVAD Implant: Findings From the Mechanical Circulatory Support: Measures of Adjustment and Quality of Life (MCS A-QOL) Study.

Study participants (n = 272) completed 12 Patient-Reported Outcomes Measurement Information System (PROMIS) physical, mental and social health measures (questionnaires) prior to implantation of a left ventricular assist device (LVAD) and again at 3 and 6 months postimplant. All but 1 PROMIS measure demonstrated significant improvement from pre-implant to 3 months; there was little change between 3 and 6 months. Because PROMIS measures were developed in the general population, patients with an LVAD, their caregivers and their clinicians can interpret the meaning of PROMIS scores in relation to the general population, helping them to monitor a return to normalcy in everyday life.

Validity of Patient-Reported Outcomes Measurement Information System Physical, Mental, and Social Health Measures After Left Ventricular Assist Device Implantation and Implications for Patient Care.

BACKGROUND: A better understanding is needed of the burdens and benefits of left ventricular assist device (LVAD) implantation on patients' physical, mental, and social well-being. The purpose of this report was to evaluate the validity of Patient-Reported Outcomes Measurement Information System (PROMIS) measures for LVAD patients and to estimate clinically important score differences likely to have implications for patient treatment or care. METHODS: Adults from 12 sites across all US geographic regions completed PROMIS measures ≥3 months post-LVAD implantation. Other patient-reported outcomes (eg, Kansas City Cardiomyopathy Questionnaire-12 item), clinician ratings, performance tests, and clinical adverse events were used as validity indicators. Criterion and construct validity and clinically important differences were estimated with Pearson correlations, ANOVA methods, and Cohen d effect sizes. RESULTS: Participants' (n=648) mean age was 58 years, and the majority were men (78%), non-Hispanic White people (68%), with dilated cardiomyopathy (55%), long-term implantation strategy (57%), and New York Heart Association classes I and II (54%). Most correlations between validity indicators and PROMIS measures were medium to large (≥0.3; p<0.01). Most validity analyses demonstrated medium-to-large effect sizes (≥0.5) and clinically important differences in mean PROMIS scores (up to 14.8 points). Ranges of minimally important differences for 4 PROMIS measures were as follows: fatigue (3-5 points), physical function (2-3), ability to participate in social roles and activities (3), and satisfaction with social roles and activities (3-5). CONCLUSIONS: The findings provide convincing evidence for the relevance and validity of PROMIS physical, mental, and social health measures in patients from early-to-late post-LVAD implantation. Findings may inform shared decision-making when patients consider treatment options. Patients with an LVAD, their caregivers, and their clinicians should find it useful to interpret the meaning of their PROMIS scores in relation to the general population, that is, PROMIS may help to monitor a return to normalcy in everyday life.

Clinician and Algorithmic Application of the 2019 and 2022 Society of Cardiovascular Angiography and Intervention Shock Stages in the Critical Care Cardiology Trials Network Registry.

BACKGROUND: Algorithmic application of the 2019 Society of Cardiovascular Angiography and Intervention (SCAI) shock stages effectively stratifies mortality risk for patients with cardiogenic shock. However, clinician assessment of SCAI staging may differ. Moreover, the implications of the 2022 SCAI criteria update remain incompletely defined. METHODS: The Critical Care Cardiology Trials Network is a multicenter registry of cardiac intensive care units (CICUs). Between 2019 and 2021, participating centers (n=32) contributed at least a 2-month snapshot of consecutive medical CICU admissions. In-hospital mortality was assessed across 3 separate staging methods: clinician assessment, Critical Care Cardiology Trials Network algorithmic application of the 2019 SCAI criteria, and a revision of the Critical Care Cardiology Trials Network application using the 2022 SCAI criteria. RESULTS: Of 9612 admissions, 1340 (13.9%) presented with cardiogenic shock with in-hospital mortality of 35.2%. Both clinician and algorithm-based staging using the 2019 SCAI criteria identified a stepwise gradient of mortality risk (stage C-E: 19.0% to 83.7% and 14.6% to 52.2%, respectively; Ptrend<0.001 for each). Clinician assignment of SCAI stages identified higher risk patients compared with algorithm-based assignment (stage D: 49.9% versus 29.3%; stage E: 83.7% versus 52.2%). Algorithmic application of the 2022 SCAI criteria, with incorporation of the vasoactive-inotropic score, more closely approximated clinician staging (mortality for stage C-E: 21.9% to 70.5%; Ptrend<0.001). CONCLUSIONS: Both clinician and algorithm-based application of the 2019 SCAI stages identify a stepwise gradient of mortality risk, although clinician-staging may better allocate higher risk patients into advanced SCAI stages. Updated algorithmic staging using the 2022 SCAI criteria and vasoactive-inotropic score further refines risk stratification.

Combining donor derived cell free DNA and gene expression profiling for non-invasive surveillance after heart transplantation.

BACKGROUND: Donor-derived cell free DNA (dd-cfDNA) and gene expression profiling (GEP) offer noninvasive alternatives to rejection surveillance after heart transplantation; however, there is little evidence on the paired use of GEP and dd-cfDNA for rejection surveillance. METHODS: A single center, retrospective analysis of adult heart transplant recipients. A GEP cohort, transplanted from January 1, 2015 through December 31, 2017 and eligible for rejection surveillance with GEP was compared to a paired testing cohort, transplanted July 1, 2018 through June 30, 2020, with surveillance from both dd-cfDNA and GEP. The primary outcomes were survival and rejection-free survival at 1 year post-transplant. RESULTS: In total 159 patients were included, 95 in the GEP and 64 in the paired testing group. There were no differences in baseline characteristics, except for less use of induction in the paired testing group (65.6%) compared to the GEP group (98.9%), P < .01. At 1-year, there were no differences between the paired testing and GEP groups in survival (98.4% vs. 94.7%, P = .23) or rejection-free survival (81.3% vs. 73.7% P = .28). CONCLUSIONS: Compared to post-transplant rejection surveillance with GEP alone, pairing dd-cfDNA and GEP testing was associated with similar survival and rejection-free survival at 1 year while requiring significantly fewer biopsies.

The Impact of the COVID-19 Pandemic on the Transplant Pharmacist Workforce.

Background: The COVID-19 pandemic has placed an unprecedented strain on the US healthcare system, greatly impacting transplant centers. Objective: The purpose of this survey was to evaluate the impact of the COVID-19 pandemic on the transplant pharmacist workforce. Methods: A survey was disseminated electronically to assess the impact of the COVID-19 pandemic on the transplant pharmacist workforce. Respondents were asked to give background regarding transplant center, patient, population, and departmental staffing. Results: There were 67 total respondents from 56 transplant centers. In response to the COVID-19 pandemic, 55% of centers reported stopping non-life saving transplants, and a majority (89%) stopped living donor transplants altogether. The banning of caregivers on-site during education, reduction of bedside education teaching, and cancelling of group teaching classes occurred at 46%, 40%, and 22% of centers, respectively. Consequently, 42% of pharmacists surveyed felt that their confidence in patient and caregiver's understanding of medications had decreased since these changes have been implemented. Conclusions: Pharmacist perception of patient and caregiver understanding of transplant medications has decreased since before the COVID-19 pandemic. As health systems strategize resource allocation throughout the pandemic, the importance of patient education must be prioritized to sustain and improve transplant outcomes.

Critical Care Cardiology Trials Network (CCCTN): a cohort profile.

AIMS: The aims of the Critical Care Cardiology Trials Network (CCCTN) are to develop a registry to investigate the epidemiology of cardiac critical illness and to establish a multicentre research network to conduct randomised clinical trials (RCTs) in patients with cardiac critical illness. METHODS AND RESULTS: The CCCTN was founded in 2017 with 16 centres and has grown to a research network of over 40 academic and clinical centres in the United States and Canada. Each centre enters data for consecutive cardiac intensive care unit (CICU) admissions for at least 2 months of each calendar year. More than 20 000 unique CICU admissions are now included in the CCCTN Registry. To date, scientific observations from the CCCTN Registry include description of variations in care, the epidemiology and outcomes of all CICU patients, as well as subsets of patients with specific disease states, such as shock, heart failure, renal dysfunction, and respiratory failure. The CCCTN has also characterised utilization patterns, including use of mechanical circulatory support in response to changes in the heart transplantation allocation system, and the use and impact of multidisciplinary shock teams. Over years of multicentre collaboration, the CCCTN has established a robust research network to facilitate multicentre registry-based randomised trials in patients with cardiac critical illness. CONCLUSION: The CCCTN is a large, prospective registry dedicated to describing processes-of-care and expanding clinical knowledge in cardiac critical illness. The CCCTN will serve as an investigational platform from which to conduct randomised controlled trials in this important patient population.

What If the Destination Is Transplant? Outcomes of Destination Therapy Patients Who Were Transplanted.

We sought to characterize patients who underwent heart transplant (HTx) following destination therapy (DT) implant in the combined ENDURANCE/ENDURANCE Supplemental Trials (DT/DT2). A post hoc analysis of the DT/DT2 trials was performed. Baseline characteristics and adverse events between the HTx and no-HTx cohorts were analyzed. Reasons for transplant were examined. Time to HTx was compared with contemporaneous HVAD BTT trial patients. Of the 604 DT/DT2 HVAD patients, 80 (13%) underwent HTx. The HTx cohort was younger (53.6 ± 11.1 vs. 65.2 ± 10.8, P < 0.0001) with fewer Caucasians (60.0% vs. 76.5%, P = 0.002), less ischemic cardiomyopathy (42.5% vs. 58.8%, P = 0.01), and atrial fibrillation (38.8% vs. 54.4%, P = 0.01). The HTx cohort had longer 6-minute walk distances (183.6 vs. 38.0 m, P = 0.02). Most HTx in DT/DT2 were categorized as elective (n = 63, 79%) and, of these, 70% were due to modification of behavioral issues and weight loss. Adverse events were the main indication for urgent HTx (n = 17, 21%). Median times to HTx were longer in DT/DT2 (550.0 days) versus BTT/lateral (285.2 days). In this post hoc analysis of the DT/DT2 trials, over 1 in 10 underwent heart transplantation within 3 years of HVAD support. In DT therapy patients, consideration for transplant following DT VAD implant may be feasible.

Concordance of Treatment Effect: An Analysis of The Society of Thoracic Surgeons Intermacs Database.

BACKGROUND: The Society of Thoracic Surgeons (STS) Intermacs Registry represents a real-world data source of durable, left ventricular assist devices that can address knowledge gaps not informed through randomized clinical trials. We sought to compare survival with contemporary left ventricular assist device technologies using multiple analytic approaches to assess concordance of treatment effects and to validate prior STS Intermacs observations. METHODS: Patients (≥19 years of age) enrolled into STS Intermacs between August 2017 and June 2019 were stratified by device type (continuous flow, centrifugal left ventricular assist device with hybrid levitation [CF-HL] or full magnetic levitation [CF-FML]). The primary outcome was 1-year survival assessed by 3 statistical methodologies (multivariable regression, propensity score matching, and instrumental variable analysis). RESULTS: Of 4448 patients, 2012 (45.2%) received the CF-HL and 2436 (54.8%) received the CF-FML. One-year survival for the CF-FML was 88% vs 79% for the CF-HL (overall P < .001), with a hazard ratio for mortality of 3.18 for the CF-HL (P < .0001) after risk adjustment. With propensity score matching (n = 1400 each cohort), 1-year survival was 87% for the CF-FML vs 80% for the CF-HL, with a hazard ratio of 3.20 for mortality with the CF-HL (P < .0001) after risk adjustment. With an instrumental variable analysis, the probability of receiving the CF-HL was associated with a hazard ratio of 3.11 (P < .0001). CONCLUSIONS: Statistical methodology using propensity score matching and instrumental variable analysis increased the robustness of observations derived from real-world data and demonstrates the feasibility of performing comparative effectiveness research using STS Intermacs. These analyses provide additional evidence supporting a survival benefit of the CF-FML vs CF-HL.

Impact of using higher-risk donor hearts for candidates with pre-transplant mechanical circulatory support.

BACKGROUND: We evaluated post-heart transplant (HTx) outcomes after use of higher-risk donor hearts for candidates supported with pre-HTx mechanical circulatory support (MCS). METHODS: In this retrospective analysis of the national United Network for Organ Sharing registry, a total of 9,915 adult candidates on MCS underwent HTx from January 1, 2010 to March 31, 2019. Multi-organ, re-transplant, and congenital heart disease patients were excluded. Higher-risk donor organs met at least one of the following criteria: left ventricular ejection fraction <50%, donor to recipient predicted heart mass ratio <0.86, donor age >55 years, or ischemic time >4 hours. Primary outcome was 1 year post-transplant survival. RESULTS: Among HTx recipients, 3688 (37.2%) received higher-risk donor hearts. Candidates supported with pre-HTx extracorporeal membrane oxygenation or biventricular assist device (n = 374, 3.8%) who received higher-risk donor hearts had comparable 1 year survival (HR: 1.14, 95% CI: [0.67-1.93], p = 0.64) to recipients of standard-risk donor hearts, when adjusted for recipient age and sex. In candidates supported with intra-aortic balloon pump (n = 1391, 14.6%), transplantation of higher-risk donor hearts did not adversely affect 1 year survival (HR: 0.80, 95% CI: [0.52-1.22], p = 0.30). Patients on durable left ventricular assist devices (LVAD) who received higher-risk donor hearts had comparable 1 year survival to continued LVAD support on the waitlist, but mortality was increased compared to those who received standard-risk donor hearts (HR: 1.37, 95% CI: [1.11-1.70], p = 0.004). CONCLUSIONS: Patients requiring pre-HTx temporary MCS who received higher-risk donor hearts had comparable 1 year post-transplant survival to those who received standard-risk donor hearts. Stable patients on durable LVADs may benefit from waiting for standard-risk donor hearts.

Cost-effectiveness and system-wide impact of using Hepatitis C-viremic donors for heart transplant.

BACKGROUND: The advent of direct-acting antiviral therapy for Hepatitis C (HCV) has made using HCV-viremic donors a viable strategy to address the donor shortage in heart transplantation. We employed a large-scale simulation to evaluate the impact and cost-effectiveness of using HCV-viremic donors for heart transplant. METHODS: We simulated detailed histories from time of listing until death for the real-world cohort of all adults listed for heart transplant in the United States from July 2014 to June 2019 (n = 19,346). This population was imputed using historical data and captures "real-world" heterogeneity in geographic and clinical characteristics. We estimated the impact of an intervention in which all candidates accept HCV+ potential donors (n = 472) on transplant volume, waitlist outcomes, and lifetime costs and quality-adjusted life years (QALYs). RESULTS: The intervention produced 232 more transplants, 132 fewer delistings due to deterioration, and 50 fewer waitlist deaths within this 5-year cohort and reduced wait times by 3% to 11% (varying by priority status). The intervention was cost-effective, adding an average of 0.08 QALYs per patient at a cost of $124 million ($81,892 per QALY). DAA therapy and HCV care combined account for 11% this cost, with the remainder due to higher costs of transplant procedures and routine post-transplant care. The impact on transplant volume varied by blood type and region and was correlated with donor-to-candidate ratio (ρ = 0.71). CONCLUSIONS: Transplanting HCV+ donor hearts is likely to be cost-effective and improve waitlist outcomes, particularly in regions and subgroups experiencing high donor scarcity.